ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2022
Integrating artificial intelligence in pathology: a qualitative interview study of users' experiences and expectations.
Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 22 papers, 4 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 4 syntheses or guidelines pooled it, 48 citations in OpenAlex.
- Ethical concerns of AI in healthcare: A systematic review of qualitative studies.Nursing ethics · 2026Pooled it
- Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.BMC health services research · 2025Pooled it
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Experience of Health Care Professionals Using Digital Tools in the Hospital: Qualitative Systematic Review.JMIR human factors · 2023Pooled it
- Artificial intelligence in pathology: a framework for preserving brain capital in the diagnostic apex.Croatian medical journal · 2026Article
- Artificial intelligence in genitourinary pathology.Histopathology · 2026Review
- Foundation Models in Cancer Pathology: Techniques, Applications, and Future Directions.Research (Washington, D.C.) · 2026Review
- Attitudes toward artificial intelligence in pathology: a survey-based study of pathologists in northern India.Journal of pathology and translational medicine · 2025Article
- Practical implementation of AI in a non-academic, non-commercial Pathology laboratory: Real world experience and lessons learned.Histopathology · 2025Review
- Streamlining a Patchwork - Exploring the Challenges of Digital Transformation in Pathology: Ethnographic Study.Journal of medical Internet research · 2025Article
- Development and clinical validation of deep learning-based immunohistochemistry prediction models for subtyping and staging of gastrointestinal cancers.BMC gastroenterology · 2025Article
- Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with artificial intelligence algorithms.Journal of clinical pathology · 2025Article
- Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts.Journal of medical Internet research · 2025Article
- The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.JMIR human factors · 2024Article
- Human-machine interaction in computational cancer pathology.ESMO real world data and digital oncology · 2024Review
- Stakeholder perspectives towards diagnostic artificial intelligence: a co-produced qualitative evidence synthesis.EClinicalMedicine · 2024Review
- Insights from semi-structured interviews on integrating artificial intelligence in clinical chemistry laboratory practices.BMC medical education · 2024Article
- Artificial Intelligence in Bone Marrow Histological Diagnostics: Potential Applications and Challenges.Pathobiology : journal of immunopathology, molecular and cellular biology · 2024Review
- Investigating the Impact of Automation on the Health Care Workforce Through Autonomous Telemedicine in the Cataract Pathway: Protocol for a Multicenter Study.JMIR research protocols · 2023Article
- Democratising or disrupting diagnosis? Ethical issues raised by the use of AI tools for rare disease diagnosis.SSM. Qualitative research in health · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent progress in the development of artificial intelligence (AI) has sparked enthusiasm for its potential use in pathology. As pathology labs are currently starting to shift their focus towards AI implementation, a better understanding how AI tools can be optimally aligned with the medical and social context of pathology daily practice is urgently needed. Strikingly, studies often fail to mention the ways in which AI tools should be integrated in the decision-making processes of pathologists, nor do they address how this can be achieved in an ethically sound way. Moreover, the perspectives of pathologists and other professionals within pathology concerning the integration of AI within pathology remains an underreported topic. This article aims to fill this gap in the literature and presents the first in-depth interview study in which professionals' perspectives on the possibilities, conditions and prerequisites of AI integration in pathology are explicated. The results of this study have led to the formulation of three concrete recommendations to support AI integration, namely: (1) foster a pragmatic attitude toward AI development, (2) provide task-sensitive information and training to health care professionals working in pathology departments and (3) take time to reflect upon users' changing roles and responsibilities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.